Methods and systems for obtaining reconstructed low-frequency seismic data for determining a subsurface feature

A system, comprising:

• a processor;
• and
• a memory storing instructions executable by the processor,
• wherein the processor is configured to;
• determine an initial training velocity model;
• train a machine learning model based on first training seismic data and second training seismic data generated from the training velocity model, the first training seismic data corresponding to one or more first frequencies, the second training seismic data corresponding to one or more second frequencies, the one or more second frequencies being lower than the one or more first frequencies;
• obtain, based on measured seismic data and the machine learning model, reconstructed seismic data corresponding to the one or more second frequencies;
• generate a velocity model based on the measured seismic data, the reconstructed seismic data, and a full waveform inversion (FWI);
• and
• when the generated velocity model does not satisfy a preset condition, update the training velocity model based on the generated velocity model, to obtain updated reconstructed seismic data for determining a subsurface feature.

A non-transitory computer-readable storage medium having stored therein instructions that, when executed by a processor of a device, cause the device to perform operations comprising:

• determining an initial training velocity model;
• training a machine learning model based on first training seismic data and second training seismic data generated from the training velocity model, the first training seismic data corresponding to one or more first frequencies, the second training seismic data corresponding to one or more second frequencies, the one or more second frequencies being lower than the one or more first frequencies;
• obtaining, based on measured seismic data and the machine learning model, reconstructed seismic data corresponding to the one or more second frequencies;
• generating a velocity model based on the measured seismic data, the reconstructed seismic data, and a full waveform inversion (FWI);
• and
• when the generated velocity model does not satisfy a preset condition, updating the training velocity model based on the generated velocity model, to obtain updated reconstructed seismic data for determining a subsurface feature.